Advances in computing hardware and software, as well as computing networks and network services, have bolstered growth of Internet-based shopping and delivery. Online shopping, in turn, has fostered the use of “subscription”-based delivery computing services with an aim to provide convenience to consumers. In particular, a user becomes a subscriber when associated with a subscriber account, which is typically implemented on a remote server for a particular retailer. In exchange for electronic payment, which is typically performed automatically, a retailer ships a specific product (or provides access to a certain service) at periodic times, such as every three (3) months. With conventional online subscription-based ordering, consumers need not plan to reorder to conveniently replenish supplies of a product.
However, conventional approaches to provide subscription-based order fulfillment, while functional, suffer a number of other drawbacks. Generally, traditional subscription-based ordering has evolved from periodic types of payment, regardless of the use of products or services. For example, a number of retail subscription models originate from those similar to DVD delivery subscription services and digital download services, which typically provide access to products as “rentals.” Thus, access is independent relative to consumption or usage. These types of subscription models, therefore, are generally not well-suited for application to non-periodic consumption rates or depletable products (e.g., product usage depletes some or all of the product).
Further, traditional subscription-based ordering relies on a user to manually determine a quantity and a time period between replenishing shipments, after which the quantity is shipped after each time period elapses. Essentially, subscribers receive products on “auto-pilot.” The different rates of usage of different subscribers generally are not well-reflected in the shipment periods with which subscriptions are established. One prevalent consequence of mismatches between time periods for delivering subscribed products and consumption rates by consumers is that, over time, the supply of a subscribed item is either over-delivered or under-delivered. An oversupply of subscribed product typically degrades consumer experience due to a number of reasons. For example, subscribers may believe that a retailer is “over-billing” the customer for unneeded products. Similarly, an under-supply of subscribed product may give to frustration and friction that an expected subscribed product is scarce or unavailable.
Online retailers and merchants may experience similar consequences due to mismatching of delivery times and consumption rates, but at an aggregate level of subscribers. In the aggregate, the mismatches may cause either overstocking or understocking of inventory of the online retailers and merchants. Fluctuations in inventory may cause non-beneficial consumption of resources and time. Note, too, that the computing systems of online retailers and merchants are not well-adapted to address the above-described mismatching phenomena when ordering, shipping, and performing inventory management.
In some conventional approaches, online retailers and merchants may aim to set delivery rates of subscribed products to optimize conversion rates (e.g., rates at which a user performs an action after vising a web page), revenue, or other metrics that are designed for online retailers and merchants rather than customers. Thus, some conventional metrics are not well-suited to correlate accurately how a product or service is consumed or depleted.
Thus, what is needed is a solution for facilitating techniques to adaptively schedule items for automatic distribution of items, without the limitations of conventional techniques.